MAT

b33d_562f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom usually one less than the number of observed categories (rows in the table) alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_c29c

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_3893

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_8419

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets MAT

b33d_2c1f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_d1c4

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ MAT

b33d_fe10

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α standard cutoff probability used to determine statistic significance critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom usually one less than the number of observed categories (rows in the table) null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern MAT

b33d_a924

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_b846

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use MAT

b33d_d996

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_7492

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ level of significance, α biologists use a probability of 0.05 (5%) for this value chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets MAT

b33d_94a6

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported p-value the smaller this number, the bigger the chi-square (χ²) test statistic degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_8322

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom represents how many independent values can vary after constraints are applied p-value the probability of getting a result that is either the same or more extreme than the actual observations null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_0824

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test MAT

b33d_5db3

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_f4c9

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_0293

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use MAT

b33d_eda4

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported chi-square (χ²) test statistic the bigger this number, the smaller the p-value level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_4921

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test p-value the smaller this number, the bigger the chi-square (χ²) test statistic level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_b34b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported MAT

b33d_3d2e

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α p-value the probability of getting a result that is either the same or more extreme than the actual observations level of significance, α biologists use a probability of 0.05 (5%) for this value degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_e676

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α biologists use a probability of 0.05 (5%) for this value p-value the smaller this number, the bigger the chi-square (χ²) test statistic degrees of freedom usually one less than the number of observed categories (rows in the table) alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern MAT

b33d_627e

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one p-value the probability of getting a result that is either the same or more extreme than the actual observations critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern MAT

b33d_de35

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom usually one less than the number of observed categories (rows in the table) null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_d073

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α standard cutoff probability used to determine statistic significance MAT

b33d_348d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value the smaller this number, the bigger the chi-square (χ²) test statistic level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_53cb

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary after constraints are applied null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_5d28

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test level of significance, α standard cutoff probability used to determine statistic significance null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_406b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_1861

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_1d4c

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ MAT

b33d_162b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the smaller this number, the bigger the chi-square (χ²) test statistic critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use MAT

b33d_0507

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom usually one less than the number of observed categories (rows in the table) null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test p-value the probability of getting a result that is either the same or more extreme than the actual observations critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate MAT

b33d_255f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value the probability of getting a result that is either the same or more extreme than the actual observations critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_6c67

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

b33d_544d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate degrees of freedom usually one less than the number of observed categories (rows in the table) null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_f49c

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ p-value the probability of getting a result that is either the same or more extreme than the actual observations degrees of freedom represents how many independent values can vary after constraints are applied chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets MAT

b33d_81b0

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values critical value found in a table for a given degrees of freedom and level of significance, α chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_1f5a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

b33d_86db

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate MAT

b33d_ab8f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern MAT

b33d_de5a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_2a82

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets degrees of freedom usually one less than the number of observed categories (rows in the table) critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_06ef

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α biologists use a probability of 0.05 (5%) for this value critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_a0ec

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported critical value found in a table for a given degrees of freedom and level of significance, α p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_9567

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported MAT

b33d_759d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom usually one less than the number of observed categories (rows in the table) critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported MAT

b33d_40eb

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ p-value the smaller this number, the bigger the chi-square (χ²) test statistic level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_2835

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_1611

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value chi-square (χ²) test statistic the bigger this number, the smaller the p-value degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use MAT

b33d_5a65

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α standard cutoff probability used to determine statistic significance alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_cab7

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test p-value the smaller this number, the bigger the chi-square (χ²) test statistic level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_824d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the probability of getting a result that is either the same or more extreme than the actual observations critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom usually one less than the number of observed categories (rows in the table) level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported MAT

b33d_c555

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_f116

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test MAT

b33d_48b4

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom usually one less than the number of observed categories (rows in the table) chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_1aff

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the bigger this number, the smaller the p-value critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_aee7

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use MAT

b33d_d749

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom represents how many independent values can vary after constraints are applied alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test MAT

b33d_1d04

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom represents how many independent values can vary after constraints are applied MAT

b33d_46d1

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom usually one less than the number of observed categories (rows in the table) chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_7dc0

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported p-value the probability of getting a result that is either the same or more extreme than the actual observations chi-square (χ²) test statistic the bigger this number, the smaller the p-value critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_d4b3

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_d388

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern degrees of freedom usually one less than the number of observed categories (rows in the table) chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_33c5

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets level of significance, α standard cutoff probability used to determine statistic significance p-value the probability of getting a result that is either the same or more extreme than the actual observations critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_099f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value the smaller this number, the bigger the chi-square (χ²) test statistic MAT

b33d_a572

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_690b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_8022

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_a7ca

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α chi-square (χ²) test statistic the bigger this number, the smaller the p-value p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

b33d_b328

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_d3f1

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data level of significance, α biologists use a probability of 0.05 (5%) for this value critical value found in a table for a given degrees of freedom and level of significance, α MAT

b33d_9070

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern critical value the cutoff used to compare against the observed chi-square (χ²) test statistic chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test MAT

b33d_0690

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α standard cutoff probability used to determine statistic significance degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_64f1

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value the probability of getting a result that is either the same or more extreme than the actual observations degrees of freedom represents how many independent values can vary after constraints are applied alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern MAT

b33d_fae4

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom usually one less than the number of observed categories (rows in the table) p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test MAT

b33d_19fb

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α standard cutoff probability used to determine statistic significance chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_cc49

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value the probability of getting a result that is either the same or more extreme than the actual observations null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom usually one less than the number of observed categories (rows in the table) level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not MAT

b33d_77e9

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate level of significance, α standard cutoff probability used to determine statistic significance chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test MAT

b33d_7b20

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets MAT

b33d_7ad4

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom usually one less than the number of observed categories (rows in the table) chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value the smaller this number, the bigger the chi-square (χ²) test statistic alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test MAT

b33d_d480

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data critical value found in a table for a given degrees of freedom and level of significance, α p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_761b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_5c4a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ degrees of freedom usually one less than the number of observed categories (rows in the table) null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_f561

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_1e81

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use p-value the smaller this number, the bigger the chi-square (χ²) test statistic level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ chi-square (χ²) test statistic the bigger this number, the smaller the p-value alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_e4dc

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom usually one less than the number of observed categories (rows in the table) null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

b33d_428a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom represents how many independent values can vary after constraints are applied p-value the probability of getting a result that is either the same or more extreme than the actual observations critical value found in a table for a given degrees of freedom and level of significance, α MAT

b33d_1e00

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value the smaller this number, the bigger the chi-square (χ²) test statistic level of significance, α standard cutoff probability used to determine statistic significance chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_a751

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a chi-square (χ²) test statistic the bigger this number, the smaller the p-value degrees of freedom represents how many independent values can vary after constraints are applied alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_b12e

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data p-value the smaller this number, the bigger the chi-square (χ²) test statistic MAT

b33d_3c24

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α standard cutoff probability used to determine statistic significance p-value the smaller this number, the bigger the chi-square (χ²) test statistic critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ degrees of freedom represents how many independent values can vary after constraints are applied chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets MAT

b33d_471a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_948c

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α standard cutoff probability used to determine statistic significance MAT

b33d_771f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate level of significance, α biologists use a probability of 0.05 (5%) for this value critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value the smaller this number, the bigger the chi-square (χ²) test statistic MAT

b33d_b54b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom represents how many independent values can vary after constraints are applied p-value the smaller this number, the bigger the chi-square (χ²) test statistic chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_6ed9

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_a30d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_2292

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom represents how many independent values can vary after constraints are applied level of significance, α standard cutoff probability used to determine statistic significance critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets MAT

b33d_49bc

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern degrees of freedom represents how many independent values can vary after constraints are applied chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_1497

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_25d8

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom represents how many independent values can vary after constraints are applied chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_0d1b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom represents how many independent values can vary after constraints are applied MAT

b33d_7e63

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a degrees of freedom represents how many independent values can vary after constraints are applied level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_d2dd

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_bd4a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ MAT

b33d_fcf7

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom usually one less than the number of observed categories (rows in the table) critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_ab94

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ critical value found in a table for a given degrees of freedom and level of significance, α MAT

b33d_3bd9

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_960f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a p-value the probability of getting a result that is either the same or more extreme than the actual observations null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_13bf

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary after constraints are applied null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_42cb

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported degrees of freedom usually one less than the number of observed categories (rows in the table) chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test MAT

b33d_f316

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_4012

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ degrees of freedom represents how many independent values can vary after constraints are applied alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_04fa

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern level of significance, α standard cutoff probability used to determine statistic significance MAT

b33d_7779

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom represents how many independent values can vary after constraints are applied p-value the smaller this number, the bigger the chi-square (χ²) test statistic level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported MAT

b33d_8a1a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value the smaller this number, the bigger the chi-square (χ²) test statistic degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_a12b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_6fac

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one critical value found in a table for a given degrees of freedom and level of significance, α p-value the smaller this number, the bigger the chi-square (χ²) test statistic alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_2898

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_584f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value found in a table for a given degrees of freedom and level of significance, α level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data degrees of freedom represents how many independent values can vary after constraints are applied p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_98e0

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use MAT

b33d_b816

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_9aae

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ MAT

b33d_ff65

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ degrees of freedom represents how many independent values can vary after constraints are applied MAT

b33d_e90f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_c06f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use level of significance, α standard cutoff probability used to determine statistic significance critical value found in a table for a given degrees of freedom and level of significance, α p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_4d33

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not degrees of freedom represents how many independent values can vary after constraints are applied critical value the cutoff used to compare against the observed chi-square (χ²) test statistic chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test MAT

b33d_e984

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom usually one less than the number of observed categories (rows in the table) critical value the cutoff used to compare against the observed chi-square (χ²) test statistic chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ MAT

b33d_c5ee

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ MAT

b33d_0601

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported chi-square (χ²) test statistic the bigger this number, the smaller the p-value p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_553a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_9ea6

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_773f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom usually one less than the number of observed categories (rows in the table) critical value found in a table for a given degrees of freedom and level of significance, α chi-square (χ²) test statistic the bigger this number, the smaller the p-value level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate MAT

b33d_f123

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_31bd

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_8ff9

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern level of significance, α standard cutoff probability used to determine statistic significance degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_e1d3

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_59aa

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported degrees of freedom represents how many independent values can vary after constraints are applied MAT

b33d_3243

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_4363

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ chi-square (χ²) test statistic the bigger this number, the smaller the p-value level of significance, α biologists use a probability of 0.05 (5%) for this value alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test MAT

b33d_10fb

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom usually one less than the number of observed categories (rows in the table) alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_d968

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the smaller this number, the bigger the chi-square (χ²) test statistic chi-square (χ²) test statistic the bigger this number, the smaller the p-value critical value found in a table for a given degrees of freedom and level of significance, α level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test MAT

b33d_eeea

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_b189

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test degrees of freedom represents how many independent values can vary after constraints are applied null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_e5da

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α biologists use a probability of 0.05 (5%) for this value MAT

b33d_7cfd

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ p-value the probability of getting a result that is either the same or more extreme than the actual observations level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets degrees of freedom represents how many independent values can vary after constraints are applied MAT

b33d_36f4

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the probability of getting a result that is either the same or more extreme than the actual observations degrees of freedom represents how many independent values can vary after constraints are applied chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate MAT

b33d_2af9

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value the probability of getting a result that is either the same or more extreme than the actual observations alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use MAT

b33d_ce3b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_870e

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the smaller this number, the bigger the chi-square (χ²) test statistic critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α standard cutoff probability used to determine statistic significance alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_fffe

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α MAT

b33d_0e71

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a degrees of freedom represents how many independent values can vary after constraints are applied level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_0f42

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern MAT

b33d_797b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ MAT

b33d_98f8

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported critical value found in a table for a given degrees of freedom and level of significance, α p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_d420

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_a4ec

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported MAT

b33d_f19d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test p-value the smaller this number, the bigger the chi-square (χ²) test statistic critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported MAT

b33d_1ddd

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_4a48

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one p-value the smaller this number, the bigger the chi-square (χ²) test statistic critical value the cutoff used to compare against the observed chi-square (χ²) test statistic chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_d023

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported degrees of freedom usually one less than the number of observed categories (rows in the table) chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_09e4

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test MAT

b33d_a338

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern p-value the smaller this number, the bigger the chi-square (χ²) test statistic chi-square (χ²) test statistic the bigger this number, the smaller the p-value level of significance, α standard cutoff probability used to determine statistic significance critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ MAT

b33d_ef32

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern level of significance, α standard cutoff probability used to determine statistic significance degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_fefa

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom represents how many independent values can vary after constraints are applied chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_3fa3

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom usually one less than the number of observed categories (rows in the table) alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_616f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_7a6b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value the smaller this number, the bigger the chi-square (χ²) test statistic alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_ec1a

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom represents how many independent values can vary after constraints are applied level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data MAT

b33d_51fb

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_fbde

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a degrees of freedom usually one less than the number of observed categories (rows in the table) alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_22e1

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one MAT

b33d_707f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values p-value the smaller this number, the bigger the chi-square (χ²) test statistic chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_eb0d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported degrees of freedom usually one less than the number of observed categories (rows in the table) critical value found in a table for a given degrees of freedom and level of significance, α chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test MAT

b33d_2d28

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ level of significance, α biologists use a probability of 0.05 (5%) for this value alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_6cd3

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ degrees of freedom this number determines which row of the chi-square (χ²) critical value table you should use p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values MAT

b33d_abb2

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_299f

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value p-value the probability of getting a result that is either the same or more extreme than the actual observations degrees of freedom represents how many independent values can vary after constraints are applied level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_891d

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test p-value the smaller this number, the bigger the chi-square (χ²) test statistic null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not chi-square (χ²) test statistic the bigger this number, the smaller the p-value MAT

b33d_6ae9

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_8299

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the smaller this number, the bigger the chi-square (χ²) test statistic chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test level of significance, α standard cutoff probability used to determine statistic significance degrees of freedom represents how many independent values can vary after constraints are applied MAT

b33d_d738

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value the probability of getting a result that is either the same or more extreme than the actual observations level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test critical value found in a table for a given degrees of freedom and level of significance, α MAT

b33d_fd1b

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_4283

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a critical value found in a table for a given degrees of freedom and level of significance, α MAT

b33d_d5ec

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value a small value suggests the observed data are NOT consistent with the null hypothesis, H₀ alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test level of significance, α a constant probability that provides a cutoff for falsification of the null hypothesis, H₀ null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_9952

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern critical value found in a table for a given degrees of freedom and level of significance, α null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom usually one less than the number of observed categories (rows in the table) MAT

b33d_a480

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_9bc8

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α biologists use a probability of 0.05 (5%) for this value chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test degrees of freedom usually one less than the number of observed categories (rows in the table) p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_56f6

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate level of significance, α standard cutoff probability used to determine statistic significance degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test MAT

b33d_b886

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets p-value the probability of getting a result that is either the same or more extreme than the actual observations MAT

b33d_8b6c

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic the bigger this number, the smaller the p-value critical value found in a table for a given degrees of freedom and level of significance, α degrees of freedom represents how many independent values can vary after constraints are applied alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_3db0

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test chi-square (χ²) test statistic if this value is large, then there is stronger evidence to support the alternative hypothesis, H_a p-value the smaller this number, the bigger the chi-square (χ²) test statistic alternative hypothesis, H_a this hypothesis represents a deviation or bias from the expected pattern MAT

b33d_cad0

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data degrees of freedom in most chi-square (χ²) tests, it is the number of observed categories (rows in the table) minus one alternative hypothesis, H_a we aim to support this hypothesis in our chi-square (χ²) test critical value the cutoff used to compare against the observed chi-square (χ²) test statistic MAT

b33d_0bb8

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a degrees of freedom represents how many independent values can vary after constraints are applied level of significance, α biologists use a probability of 0.05 (5%) for this value null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test alternative hypothesis, H_a if the null hypothesis, H₀ cannot be supported , then this opposing hypothesis is supported MAT

b33d_3f50

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the bigger this number, the smaller the p-value p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a level of significance, α a fixed probability cutoff whether the null hypothesis, H₀ can be or cannot be supported critical value the boundary of how extreme a test statistic we need to support the null hypothesis, H₀ null hypothesis, H₀ we want to faill to support this hypothesis in our chi-square (χ²) test MAT

b33d_1dd8

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

null hypothesis, H₀ we attempt to find evidence against this hypothesis in our chi-square (χ²) test level of significance, α the fixed probability for whether or NOT the null hypothesis, H₀ can be supported chi-square (χ²) test statistic a measure of the discrepancy between the observed and expected data sets alternative hypothesis, H_a for this hypothesis, the expected values are often impossible to calculate p-value if this value is small, then there is stronger evidence to support the alternative hypothesis, H_a MAT

b33d_d1e1

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

chi-square (χ²) test statistic the sum of the normalized square difference between observed and expected data level of significance, α the statistical cutoff of the result for the null hypothesis, H₀ to be supported or not null hypothesis, H₀ this hypothesis makes it easier to calculate the expected values degrees of freedom represents how many independent values can vary after constraints are applied p-value the smaller this number, the bigger the chi-square (χ²) test statistic MAT

b33d_d6a8

Match each of the following chi-square (χ²) terms with their corresponding definitions.

Note: Each choice will be used exactly once.

critical value the cutoff used to compare against the observed chi-square (χ²) test statistic p-value the smaller this number, the bigger the chi-square (χ²) test statistic degrees of freedom represents how many independent values can vary after constraints are applied alternative hypothesis, H_a we are attempting to support this hypothesis indirectly by using the chi-square (χ²) test level of significance, α biologists use a probability of 0.05 (5%) for this value